7.2 Ingenieurbau
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- Ground vibration (6)
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Organisationseinheit der BAM
- 7.2 Ingenieurbau (83) (entfernen)
Am Beispiel von mehreren Bauvorhaben wird untersucht, mit welchen Unsicherheiten bei der Anwendung von Korrelationen zwischen Sondierergebnissen und Scherwellengeschwindigkeit zur Beschreibung der dynamischen Bodeneigenschaften gerechnet werden muss. Die Auswertung von Korrelationen aus der Literatur zur Abschätzung der Scherwellengeschwindigkeit aus Drucksondierdaten zeigt, dass bei homogenen Sandböden die Verteilung der Scherwellengeschwindigkeit über die Tiefe sehr gut wiedergegeben werden kann. Die Korrelationen haben dabei die Tendenz, den tatsächlichen Wert zu überschätzen. In den vorliegenden Fällen haben sich Überschätzungen zwischen 20 % und 50 % ergeben. Mit zunehmendem Feinkornanteil werden die Unsicherheiten aus den Korrelationen jedoch größer.
Die natürliche Variabilität des Bodens bewirkt, dass jegliche in-situ Messung dynamischer Bodenparameter stets nur den Untersuchungsort beschreiben, und jede Verwendung für benachbarte Orte bereits eine Extrapolation ist. Gleichzeitig ist die Ermittlung von Bodeneigenschaften in-situ mit erheblichen Kosten verbunden, insbesondere bei Standorten wie z. B. Offshore-Windparks. Im innerstädtischen Raum sind seismische Messungen wegen der vorhandenen Bebauung und Flächenversiegelungen nur eingeschränkt möglich. Es bietet sich daher an, indirekte Methoden auf Basis von Drucksondierungen anzuwenden, weil diese Untersuchungen inzwischen zum Standardrepertoire selbst bei kleineren Bauvorhaben gehören.
Der neue nationale Anhang zu DIN EN 1998-1 erlaubt die Anwendung von Korrelationen zwischen Sondierergebnissen und dynamischen Bodeneigenschaften zur Anwendung bei seismischen Standortanalysen. Es werden jedoch keine Hinweise zur Auswahl geeigneter Korrelationen gegeben. Mit ISO/TS 14837-32 liegt ein Standard vor, in dem sogar für sandartigen Boden und tonartigen Boden zwei konkrete Korrelationen zur Anwendung vorgeschlagen werden. Dasselbe gilt für den Entwurf des Eurocode 7-2, prEN 1997-2 von 2022.
Untersuchungen zeigen, dass seismische Verfahren, wenn sie nicht unter Labor-Freifeldbedingungen durchgeführt werden, signifikante Streuungen aufweisen. Sofern statistische Korrelationen eine Streuung aufweisen, die in derselben Größenordnung liegen wie Ergebnisse seismischer Verfahren, können beide Verfahren in Grundsatz alternativ eingesetzt werden.
Wir zeigen, dass bei homogenen ausgeprägt sandartigen Böden mit statistisch ermittelten Korrelationen die dynamischen Bodensteifigkeiten mit einer Genauigkeit abgeschätzt werden können, die mit der Ungenauigkeit der seismischen Verfahren übereinstimmt. Mit zunehmenden Feinkornanteil werden die Unsicherheiten der statistischen Korrelationen größer. Bei stark überkonsolidierten glazialen Böden sollte von der Anwendung empirischer Korrelationen Abstand genommen werden.
Owners or operators of offshore wind farms perform inspections to collect information on the condition of the wind turbine support structures and perform repairs if required. These activities are costly and should be optimized. Risk-based methods can be applied to identify inspection and repair strategies that ensure an optimal balance between the expected total service life cost of inspection and repair, and the achieved risk reduction. Such an optimization requires explicit modeling of repairs. In this paper, the impact of different repair models on the results of a risk-based optimization of inspection and repair strategies is quantified in a numerical example considering a jacket-type steel frame subject to high-cycle fatigue. The example showed that, in this specific application, there is no need for detailed modeling of the behavior of repaired welded connections.
In this contribution, we consider two applications in which probabilistic approaches can potentially complement or enhance the design and assessment of offshore wind turbine foundations. First, we illustrate in a numerical example that probabilistic modelling can be helpful in dealing with chang-es in turbine locations during the planning phase of an offshore wind farm. In this case, spatial probabilistic modelling of the ground conditions enables (a) an inference of the soil properties at the modified turbine location from field data collected at different locations across an offshore wind farm site and (b) an optimisation of further site investigations. Second, we discuss the uncer-tainties and risks associated with the installation of large diameter monopiles in soils with hetero-geneities such as strong layers and/or embedded boulders. Subsequently, we present a concept for modelling, understanding, and managing these risks based on a probabilistic model of the subgrade conditions, monopile, and subgrade-pile-interaction.
Identifying optimal inspection and repair strategies for offshore jacket structures is a challenging task. We pre-sent an approach, which is based on recent developments in the field of risk-based operation and maintenance planning at the structural system level. The approach utilizes heuristics to define inspection and repair strate-gies at the system level and to reduce the search space of possible strategies. For each defined strategy, the expected service life cost of inspection, repair and failure is evaluated based on simulated inspection and re-pair histories. Subset simulation is applied to compute the conditional repair and failure probabilities required for this analysis. It also forms the basis for simulating inspection and repair histories. The strategy that mini-mizes the expected service life cost is the optimal one in the set of pre-selected strategies. The underlying condition and performance model accounts for the stochastic dependence among the deterioration states of the different structural elements and the structural redundancy. The approach is demonstrated in a case study considering a jacket-type frame. In this study, we essentially vary the inspection interval, the minimum num-ber of inspected components and the target reliability, and identify the combination that minimizes the ex-pected total service life cost.
The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic Engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the
probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability.
Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model.
Superplasticizer and Shrinkage Reducing Admixture Dosages for Microfine Cement in Grout Systems
(2019)
Grouts have numerous applications including crack repair as maintenance in construction industries. Microfine cements are intensively used for high strength mortar and grout products. They are ideal for injection grouting in structural repair. Such grouts should have suitable rheological properties to be injectable, especially those used in repair and rehabilitation. The use of superplasticizers (SP) in these products is thus becoming increasingly crucial to achieve favorable workability and viscosity properties. A difficulty in such grouts is the plastic shrinkage due to finer particles used. It is thus necessary to determine optimum SP and shrinkage reducing admixture (SRA) dosages for a microfine cement based grout. In this study, a saturation dosage was decided from two Polycarboxylate ether (PCE) based SPs in relation to neat cement using slump flow and rheological parameters. A range of grout mixtures was formulated containing micro silica (MS) and fly ash (FA), and tested for suitable rheological and mechanical parameters. Based on the results, a grout mixture with MS and FA was selected to determine optimum SRA content. According to the results, a SP dosage of 3% by weight of neat cement is sufficient to achieve saturation. The grout material including MS and FA can produce comparable properties to neat cement grout. MS is found to improve compressive strength within the range considered, whereas a higher FA content provides favourable rheological properties. Finally, a SRA dosage of 4%, which could reduce the shrinkage by about 43% after 28d days, is determined for the grout system.
Grouting is a universal repair and strengthening technique, which is constantly used for structural remediation of concrete components, trenches, mine subsidence, dam joints, restoration of masonry structures, and geological stabilizations. Having an extremely small particle size of only few microns, ultrafine cements are ideal for grouting applications due to their superior permeability and compressive strength properties of the hardened cement paste compared to that of the less-expensive, but coarser ordinary Portland cements. Supplementary cementitious materials (SCMs) are often used to replace ultrafine cement in order to modify certain properties and to reduce costs. The aim of this experimental study is to investigate the effect of three supplementary materials: microsilica (MS), fly ash (FA), and metakaolin (MK) on the workability, and mechanical properties of an ultrafine cement based grout with a constant water-binder ratio and constant superplasticizer content. Maximum percentages of replacement with ultrafine cement were 6% by volume of cement for MS and 16% for FA, and MK. In general, results suggest that the workability is improved by addition of FA, whereas is reduced, when modified with MS and MK. The compressive strength of grout after cement replacement remains comparable to that of pure cement grout. However, there is a tendency of the MS to positively affect the compressive strength opposite to FA, whereas flexural strength is positively affected by FA. Based on the results, it is evident that grouts with Hägerman cone flow more than 500 mm and compressive strength of more than 90 MPa after 28 days can be produced.
Remediation of Cracks Formed in Grouted Connections of Offshore Energy Structures under Static Loads
(2018)
The future energy demand necessitates the exploration of all potential energy sources both onshore and offshore. Global trend has shifted towards offshore energy, which can be obtained from either carbon intensive or renewable options, hence requiring structures such as rigs, platforms, and monopiles. Most of these structures adopt easily installable construction techniques, where lower foundation need to be connected with the super structure by mean of grouted composite joints. Generally, these composite connections have exterior sleeve, interior pile and infill grout. Being located in remote offshore conditions, connections can experience considerable adverse loading during their lifetimes. Degradations were reported inside similar connections, which were installed in last three decades. Besides, grouting in the offshore sites may often be proven difficult, which eventually leads to reduced capacity of connections in the long run. Thus, repair and rehabilitation of such connections should be planned ahead to minimize operational delays and costs in the future. This study aims at characterizing the nature of crack generation in grouted connections and thereby identifying the potential of repair using suitable repair material. Scaled grouted joints were manufactured using a novel mold, and connections were loaded under static load to visualize the main failure pattern. The failure mechanism and loading capacity are found compatible to previous results from earlier literature. Grouted connection was then repaired using cementitious injectable grout. The effectiveness of the repair system is also discussed.
Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system.